A European Vision for AI Call for the Establishment of a Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE)
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A European Vision for AI Call for the Establishment of a Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE) Prepared by Holger Hoos (Universiteit Leiden, The Netherlands), Morten Irgens (Oslo Metropolitan University, Norway), and Philipp Slusallek (German Research Center for Artificial Intelligence, Germany), based on discussions with many key members of the European AI Community. Find additional information about this initiative at claire-ai.org. 1. The Need for a European AI Strategy Artificial intelligence (AI) methods and technologies are posed to bring transformative change to societies and industries world-wide. The game-changing nature of AI and its role as a major driver of innovation, future growth, and competitiveness are internationally recognised. As a result, AI is at the top of national and international policy agendas around the globe. In the United States of America, huge investments in AI are made by the private sector, and a substantial governmental plan was launched in 2016, which includes significant long-term investments in AI research [1]. Similarly, in 2017, the Canadian government has started making major investments in AI research, focusing mostly on existing strength in deep learning [2]. In 2017, China released its Next Generation AI Development Plan, with the explicit goal of attaining AI supremacy by 2030 [3]. However, in terms of investment in talent, research, technology and innovation in AI, Europe lags far behind its competitors. As a result, the EU and associated countries are increasingly losing talent to academia and industry elsewhere [4]. Europe needs to play a key role in shaping how AI changes the world, and, of course, benefit from the results of AI research. The reason is obvious: AI is crucial for meeting Europe’s needs to address complex challenges as well as for positioning Europe and its nations in the global market. Europe has started to react: In April 2018, 25 countries pledged to increase national research funding for AI as part of a common “European approach” [5]. In parallel, the European Commission laid out a preliminary plan for strengthening AI across Europe [6], realising that more focussed instruments are needed beyond those planned in H2020 to turn the tide and achieve the research and innovations we need, and on the scale we need. This urgent sense of need for action was also clearly expressed in a recent open letter by a number of AI researchers, who proposed a European research centre in machine learning and related areas of AI [7]. In the following, we outline a proposal that builds on and expands on these initiatives, and, we believe, is necessary to meet their objectives. In particular, we strongly support the ambition and vision articulated in the recent EC Communication [6], and we endeavour to present a specific approach to realising it. Last updated on 30 October 2019 1 2. All of AI, all of Europe, with a Human-Centred Focus There is a pressing need for increasing Europe’s strength and position in the area of AI research. Based on extensive discussions within the community of European AI researchers, following the recent EC Communication on AI [6], a strong consensus has emerged on key aspects of a coordinated European research effort. In particular, a broad and ambitious vision is needed for European AI research to thrive and for Europe to stay competitive with other major players. The research and innovation efforts required in this context should encompass all of AI, and include all of Europe. Furthermore, by building on our existing strength in AI and commitment to European values, Europe should take a human-centred approach to AI. We call for a vision that aims to (1) have European research and innovation in artificial intelligence be amongst the best in the world, that (2) encompasses all of AI and all of Europe, and that (3) has a strong focus on human-centred AI. The best in the world. In order to meet Europe’s challenges and to secure markets, European research and innovation needs to be among the best in the world. The good news is that Europe is very well positioned: We have a strong tradition of excellence in all areas of AI, and many of the top European researchers are recognised as leading figures within the AI community and related fields of research and technology. All of AI. Artificial intelligence comprises a broad spectrum of methods and techniques, each with their own important applications. While recently, advances in machine learning techniques have enabled rapid progress across many areas of AI, future applications of AI will increasingly leverage combinations of AI techniques. It is therefore crucial that Europe builds on its existing strengths across the full spectrum of AI, covering all of machine learning, knowledge representation and reasoning, search and optimisation, planning & scheduling, multi-agent systems, natural language processing, robotics, computer vision, and other areas. A broad view of AI that includes all areas within the field is essential to meet the challenges that lie ahead of us, especially in human-centred, ethical AI, where explanations and deep understanding (of natural language, images, etc.) are essential to achieve trust between humans and machines, and to thus obtain the best solutions to the problems we face as individuals and societies. Moreover, AI researchers need to adopt a multi-disciplinary approach and work with experts from other areas, not only from mathematics, engineering and the natural sciences, but also with social scientists. All of Europe. Human talent is already a limiting factor in AI research and development in Europe. For a European initiative to succeed, it needs to attract, educate, and harness talent, and drive innovation across the continent, leveraging the strength in AI currently found in many European countries, and Last updated on 30 October 2019 2 ensuring diversity and inclusion across languages, cultures and gender. It is therefore of key importance to foster AI excellence across Europe. Human-centred AI. Artificial intelligence increasingly enables new forms of production, services, and medical treatments, but may also lead to increased bias, inequity, manipulation, invasion of privacy, and job loss [8]. We believe that responsible AI research and deployment should be strategically focussed on augmenting human capabilities, rather than replacing them, on compensating for human bias and limitations, and on serving and protecting the human and ethical values that are of core importance to European societies [9]. Research on AI in Europe thus needs to understand, anticipate, and address ethical, legal and social aspects (also known as, and in EU's Framework Programmes usually referred to as, Responsible Research and Innovation, or RRI). As AI scientists, we are keenly aware that AI is a disruptive set of technologies. Consequently, we need to act at the European level and issue a set of principles and guidelines regarding the responsible use of AI - similar to what physicists did in 1955 with the “Russell-Einstein manifesto”. This "AI manifesto" should stipulate limits of responsible use and anticipate the consequences of deploying specialised AI systems as well as of creating general, human-level AI. It should also define how to quantitatively and qualitatively assess whether AI systems or agents comply with those limits. We believe that European AI researchers are in an ideal position to play a leading role in an ambitious, global effort to address these issues and have a responsibility to exercise leadership in this area. 3. A Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE) The discussions within the community of European AI researchers have also led to a clear understanding that Europe needs not only to increase its research activity level, but also to coordinate better and collaborate more closely. This requires investment in both outstanding AI research and in structures that allow effective collaboration and transfer of results. In particular, major actions are required to develop and retain key talent and expertise in AI, and existing strength needs to be leveraged and expanded. Specifically, we call for the establishment of a Confederation of Laboratories for Artificial Intelligence Research in Europe (CLAIRE), comprising a network of centres of excellence, strategically located throughout Europe, and a new, central facility that serves as a hub, providing state-of-the-art infrastructure, and fostering the exchange of ideas and expertise. To be effective in meeting the above vision, CLAIRE should consist of the following key elements: ● A collaborative network of relevant existing and new research labs and organisations across Europe. Under the leadership of some of the top researchers in the field, this network should jointly identify fundamental research questions, discuss the most promising approaches, and help organise collaborative efforts to address them. Last updated on 30 October 2019 3 ● A selection of some of these research labs, located strategically throughout the European Economic Area and EFTA, to be designated “Centres of Excellence in AI”, should play strong regional or national roles as hubs for the members of the collaborative network in their region. ● A new facility that serves as a highly visible and vibrant focal point for the collaborative network, the “CLAIRE Hub”. Here, excellent scientific personnel at all levels and from all partners would find an outstanding research environment for AI, where they can work together, face-to-face, for periods of time (e.g., an extended version of the highly successful Leibniz Centre for Informatics in Dagstuhl, Germany). This hub should provide cutting-edge infrastructure and support, but would not have permanent scientific staff. This is a model that builds on existing strengths, brings together the still fragmented AI research activities and expertise in Europe, while at the same time creating centres of excellence and a structure that can efficiently focus research and distribute results.